One-third of Germany’s land surface area is covered by forest (around 11.4 million hectares), and thus, it characterizes the landscape. The forest is a habitat for a large number of animal and plant species, a source of raw materials, important for climate protection, and a well-being refuge for people, to name just a few of its many functions. During the annual forest condition surveys, the crown condition of German forests is assessed on the basis of field samples at fixed locations, as the crown condition of forest trees is considered an important indicator of their vitality. Since the start of the surveys in 1984, the mean crown defoliation of all tree species has increased, now averaging about 25% for all tree species. Additionally, it shows a strong rise in the rate of dieback. In 2019, the most significant changes were observed. Due to the drastic changes in recent years, efforts are being made to assess the situation of the forest using different remote sensing methods. There are now a number of freely available products provided to the public, and more will follow as a result of numerous projects in the context of earth-observation (EO)-based monitoring and mapping of the forests in Germany. In 2020, the situation regarding the use of remote sensing for the German forest was already investigated in more detail. However, these results no longer reflect the current situation. The changes of the last 3 years are the content of this publication. For this study, 84 citable research publications were thoroughly analyzed and compared with the situation in 2020. As a major result, we found a shift in the research focus towards disturbance monitoring and a tendency to cover larger areas, including national-scale studies. In addition to the review of the scientific literature, we also reviewed current research projects and related products. In congruence to the recent developments in terms of publications in scientific journals, these projects and products reflect the need for comprehensive, timely, large-area, and complementary EO-based information around forests expressed in multiple political programs. With this review, we provide an update of previous work and link it to current research activities. We conclude that there are still gaps between the information needs of forest managers who usually rely on information from field perspectives and the EO-based information products.

Wildfire risk increases following non-fire disturbance events, but this relationship is not always linear or cumulative, and previous studies are not consistent in differentiating between disturbance loops versus cascades. Previous research on disturbance interactions and their influence on forest fires has primarily focused on fire-prone regions, such as North America, Australia, and Southern Europe. In contrast, less is known about these dynamics in Central Europe, where wildfire risk and hazard are increasing. In recent years, forest disturbances, particularly windthrow, insect outbreaks, and drought, have become more frequent in Central Europe. At the same time, climate change is influencing fire weather conditions that further intensify forest fire dynamics. Here, we synthesize findings from the recent literature on disturbance interactions in Central Europe with the aim to identify disturbance-driven processes that influence the regional fire regime. We propose a conceptual framework of interacting disturbances that can be used in wildfire risk assessments and beyond. In addition, we identify knowledge gaps and make suggestions for future research regarding disturbance interactions and their implications for wildfire activity. Our findings indicate that fire risk in the temperate forests of Central Europe is increasing and that non-fire disturbances and their interactions modify fuel properties that subsequently influence wildfire dynamics in multiple ways.

In 2021, the Tajogaite Volcano erupted along the western slope of the Cumbre Vieja on the island of La Palma, Canary Islands, Spain. Volcanic tephra blanketed a substantial proportion of the island. By our estimations, approximately 23,000,000 m³ of pyroclastic ashes and more coarse-grained particles were deposited unto La Palma's land surface in addition to the lava flow. Five months following the initial eruption, we measured the depth of the new ash layer across the island. We combined this data with drone-based observations to compile a dataset comprising the point distribution of ash depth. A spatial interpolation was then performed using Inverse Distance Weighting (IDW) to estimate the ash depth across the island at a 2 m spatial resolution. The interpolation performed well, yielding a root mean squared error (RMSE) value of 0.34 and thus, the dataset offers immense reuse potential for spatial inquiries related to evolutionary traits, vegetation patterns, and vegetation response to disturbance on oceanic islands. In addition, the data can be used to test different spatial interpolation techniques in an effort to improve the accuracy achieved using IDW.

Question: Tephra deposition is one of the most critical sudden alterations caused by volcanic eruptions in ecosystems. Tephra accumulation on the ground decreases with distance from the crater. The effect of ash deposition on the seed bank and its subsequent germination success has previously been studied by removing the tephra from the soil. However, conducting controlled experiments on the effect of tephra thickness on the seed bank and its seedling emergence capacity is a new approach to tackle and quantify recruitment mechanisms. Here, we present the first experimental study of the impact of tephra layer thickness on the seed bank combined with field surveys on seedling emergence. Location: Tajogaite volcano, Cumbre Vieja Ridge, La Palma, Canary Islands. Methods: The study includes a controlled experiment and a field survey along a gradient from the volcano crater to the perimeter within the Canary Island's pine forest. In the experiment, six tephra thickness categories were used to bury seeds (1, 5, 10, 45, 75 and 150 cm) based on observatory evidence corresponding to the distance away from the crater (7, 4, 2, 1.5, 0.75 and 0.15 km, respectively). Seeds were collected from the four most characteristic endemic pine forest species, representing different seed sizes and growth forms: Pinus canariensis (Pinaceae, tree), Chamaecytisus proliferus (Fabaceae, shrub), Lotus campylocladus (Fabaceae, forb) and Cistus symphytifolius (Cystaceae, shrub). One hundred seeds of each species were used per treatment (2800 seeds). In the field survey, we randomly established six quadrats (30 × 30 m) at the same distance from the crater as indicated above. Seedlings (< 5 cm in height) from natural regeneration were counted every three months. Results: After 18 months under ash, germination in the experiment was only detected in the treatments of control (germination rate of P. canariensis = 71%, Ch. proliferus = 13%, L. campylocladus = 24%, C. symphytifolius = 1%), and at 1 cm (51%, 18%, 11%, 1%) and 5 cm (5%, 4%, 0%, 0%) of ash depth. Conclusions: The massive ashfall during this eruption completely and suddenly dysfunctionalized the seed bank as a reservoir of recruitment in areas within a radius of approximately 5 km from the crater (still buried under a 5 cm thick ash layer to date). Therefore, we provide evidence for the hypothesis that the recent volcanic eruption will profoundly change plant community dynamics and composition within large areas of the Canary Island's pine forest.

Wildfires increasingly threaten European ecosystems and communities, highlighting the necessity for effective predictive metrics to enhance fire risk management strategies. This study aims to compare the effectiveness of Vapor Pressure Deficit (VPD) and the Fire Weather Index (FWI) in forecasting wildfire occurrence and the extent of burned areas across various European forest types. Utilizing the European Forest Fire Information System (EFFIS) for comprehensive fire event data and the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) for meteorological variables, daily VPD and FWI values will be derived for multiple fire seasons spanning from 2000 to 2024.The research will explore how VPD and FWI each predict wildfire occurrence and burned area, with a focus on different forest types are categorized according to the CORINE Land Cover classification into broadleaf, conifer, and mixed forests while encompassing a range of climatic regions across Europe. VPD calculation methods are generally more straightforward and require fewer input parameters. In contrast FWI system is more complex, requiring a broader range of input data to compute its numerous indices.By comparing these two metrics across diverse forest types and biomes, the study seeks to determine the most effective indicators for wildfire prediction in Europe. The findings are intended to inform policymakers and fire management agencies, aiding in the development of targeted early warning systems and adaptive fire management strategies. This comparative assessment will contribute to a deeper understanding of the climatic drivers of wildfires and support efforts to mitigate their impacts under changing environmental conditions.